Name
Abstract | ||
|---|---|---|
Outer joins are ubiquitous in many workloads but are sensitive to load-balancing problems. Current approaches mitigate such problems caused by data skew by using (partial) replication. However, contemporary replication-based approaches (1) introduce overhead, since they usually result in redundant data movement, (2) are sensitive to parameter tuning and value of data skew and (3) typically require that one side is small. In this paper, we propose a novel parallel algorithm, Redistribution and Efficient Query with Counters (REQC), aimed at robustness in terms of size of join sides, variation in skew and parameter tuning. Experimental results demonstrate that our algorithm is faster, more robust and less demanding in terms of network bandwidth, compared to the state-of-the-art. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-09873-9_22 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Joins,Parallel algorithm,Computer science,Parallel computing,Robustness (computer science),Bandwidth (signal processing),Skew,Distributed computing | Conference | 8632 |
ISSN | Citations | PageRank |
0302-9743 | 11 | 0.54 |
References | Authors | |
20 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Long Cheng | 1 | 91 | 16.99 |
| Spyros Kotoulas | 2 | 590 | 46.46 |
| Tomas E. Ward | 3 | 104 | 19.10 |
| Georgios Theodoropoulos | 4 | 332 | 31.39 |